A two-stage detection and classification has been proposed in [1]}. They train a faster-RCNN [2]} to detect RBC and non-RBC(like trophozoite,ring etc). After the faster-RCNN will give region of interest for non-RBC cells, a separate CNN classifier has been used to classify the non-RBC cells into further classes. This system achieved an accuracy of 98% . This study lacks emphasis on field effectiveness of their algorithm because of sharp and clear images in the dataset which might not be the case in real life. Although we adopt a similar approach, the key goal of this study is to provide a benchmark on an openly available dataset.
